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Clustering by repeated data


Clustering by repeated data

By : Marshall Eubanks
Date : November 19 2020, 03:01 PM
This might help you Using networkx:
code :
import networkx

edges = [[1, 2], [2, 3], [4, 5], [6, 7], [7, 8], [9, 4], [8, 5]]

graph = networkx.Graph(edges)
print(list(networkx.connected_components(graph)))
[set([1, 2, 3]), set([4, 5, 6, 7, 8, 9])]


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OpenLayers clustering -- clustering data doesn't appear in event.feature object

OpenLayers clustering -- clustering data doesn't appear in event.feature object


By : Miguel Rodrigues
Date : March 29 2020, 07:55 AM
To fix the issue you can do It seems the trick is to remove the features from the layer and re-add them at them after the layer has been added to the map:
code :
this.observationLayer.removeFeatures(this.observationLayer.features);
this.observationLayer.addFeatures(features);
Repeated Record - Nested and Repeated Data - Java API

Repeated Record - Nested and Repeated Data - Java API


By : Andrei Tang
Date : March 29 2020, 07:55 AM
This might help you I am trying to stream repeated record field using JAVA API. It inserts the record but with null values. The data and schema I am using is from google's example for "Nested and Repeated Data" , Instead of JsonArray creating List is working as below:
code :
List<TableRow> children = new ArrayList<TableRow>();

TableRow child1 = new TableRow();
child1.set("name", "Jane");
child1.set("gender", "f");
child1.set("age", 6);       

TableRow child2 = new TableRow();
child2.set("name", "John");
child2.set("gender", "m");
child2.set("age", 15);

children.add(child1);
children.add(child2);
Clustering 3d scatter data using k-means clustering in matlab

Clustering 3d scatter data using k-means clustering in matlab


By : lolman
Date : March 29 2020, 07:55 AM
I think the issue was by ths following , I have a 3d scatter plot organized in an array. When I plot my data as a 3d scatter plot, I obtain 2 clear clusters - one smaller one on the left and one large one on the right. , Change to plot3 and add the C(:,3), This worked for me:
code :
data=rand(100,3);
data=[data;2+rand(50,3)];

opts = statset('Display','final');
[idx,C] = kmeans(data,2,'Distance','cityblock','Replicates',5,'Options',opts);
figure(1);cla;gca;hold on;
plot3(data(idx==1,1),data(idx==1,2),data(idx==1,3),'r.','MarkerSize',12)
plot3(data(idx==2,1),data(idx==2,2),data(idx==2,3),'b.','MarkerSize',12)
plot3(C(:,1),C(:,2),C(:,3),'cx','MarkerSize',15,'LineWidth',3)
legend('Cluster 1','Cluster 2','Centroids','Location','NW')
title('Cluster Assignments and Centroids');
hold off
clustering inside clustering that is nested clustering of a data table that is multiclass clustering

clustering inside clustering that is nested clustering of a data table that is multiclass clustering


By : k1mountain
Date : March 29 2020, 07:55 AM
it helps some times You will need to carefully balance thresholds in textual similarity and in numerical similarity. There won't be an easy solution, and unless you have really huge data, a manual approach may be best.
Textual similarity of short strings is highly unreliable.
Cylindrical Clustering in R - clustering timestamp with other data

Cylindrical Clustering in R - clustering timestamp with other data


By : Eeldritch
Date : March 29 2020, 07:55 AM
Hope this helps Here is such a mapping of h to m where h is the time in hours (and fraction of an hour). Then we try kmeans and at least in this test it seems to work:
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